Embodiments of the present invention generally relate to engine after-treatment control systems. More particularly, embodiments of the present invention relate to adapting a controller using an estimated after-treatment system variation.
Selective catalytic reduction (SCR) systems typically are configured to provide one or more catalyst elements that, with the aid of a reductant, covert nitrogen oxides (NOx) in exhaust gases into nitrogen (N2) and water. The reductant, such as, for example, ammonia (NH3), may be injected into the exhaust gas upstream of the SCR catalyst. Typically, engine after-treatment systems attempt to inject a sufficient quantity of reductant into the exhaust gas necessary for the conversion of a predetermined amount of the NOx in the exhaust gas so as to prevent NOx slippage without incurring reductant slippage.
Numerous variable parameters affect the determination of the quantity of reductant that is to be injected into exhaust gases. Further, at least some of these variables may change during operation of the engine, such as, for example, due to changes in engine operating and/or environmental conditions. Additionally, at least some of these changes may occur relatively rapidly and/or be relatively short in duration, thereby allowing for a relatively short time period for the detection of such changes and to respond accordingly. Conversely, other changes, such as, for example, catalyst aging, may be more gradual, thereby requiring both monitoring over relatively long periods of time and adaptation strategies that are different than strategies that address variations that are more transient in nature. Further, the inability to accurately, and timely, detect and/or predict such shorter and longer term changes or variations may hinder the ability of the after-treatment system to relatively effectively treat NOx in exhaust gases, and thereby may increase the occurrence of NOx slippage or reductant slippage.
The operation of after-treatment systems is often controlled, at least in part, by controllers. Traditional controllers often have feed-back controllers to compensate for both high and low frequency variations or uncertainties in the after-treatment system. For example, the feed-back controller may receive a plurality of information relating to high frequency variations in characteristics of the engine system, including, for example, sensed, monitored, or predicted characteristics or conditions of the after-treatment system that have occurred or otherwise extend over relatively short periods of time, such as, for example, seconds or minutes. Additionally, the feed-back controller may also receive a plurality of information relating to low frequency variations in characteristics of the engine system, such as, for example, variations that reflect changes in the after-treatment system that have occurred over longer periods of time then the high frequency variations, such as, for example, variations that have occurred over the course of hours or days. Information pertaining to such low frequency variations may be more indicative of the performance of at least certain aspects of the after-treatment system than information reflecting high frequency variations.
As traditional feed-back controllers typically address both high and low frequency variations together, the control authority of feed-back controllers are typically limited, as they usually seek a balance between the impact adjustments on both high and low frequency variations. Such an attempt at attaining a balance between both high and low frequency variations may be implemented at least in part by limiting the control authority of the feed-back controller. But limitations on the control authority may adversely impact the accuracy of the information and/or commands provided by the feed-back controller. Additionally, the robustness of the feed-back controller may also be adversely impacted, as the feed-back controller is analyzing, addressing, and/or balancing both low and high frequency variations.